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Characterizing probability density distributions for household electricity load profiles from high-resolution electricity use data

机译:从高分辨率用电量数据表征家庭用电负荷曲线的概率密度分布

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This paper presents a high-resolution bottom-up model of electricity use in an average household based on fit to probability distributions of a comprehensive high-resolution household electricity use data set for detached houses in Sweden. The distributions used in this paper are the Weibull distribution and the Log-Normal distribution. These fitted distributions are analyzed in terms of relative variation estimates of electricity use and standard deviation. It is concluded that the distributions have a reasonable overall goodness of fit both in terms of electricity use and standard deviation. A Kolmogorov-Smirnov test of goodness of fit is also provided. In addition to this, the model is extended to multiple households via convolution of individual electricity use profiles. With the use of the central limit theorem this is analytically extended to the general case of a large number of households. Finally a brief comparison with other models of probability distributions is made along with a discussion regarding the model and its applicability.
机译:本文基于瑞典独立式住宅的高分辨率家庭综合用电数据集的概率分布拟合,提出了一个普通家庭的高分辨率自下而上模型。本文使用的分布是韦布尔分布和对数正态分布。根据电力使用和标准偏差的相对变化估计来分析这些拟合的分布。结论是,就用电量和标准偏差而言,这些分布具有合理的总体拟合优度。还提供了拟合优度的Kolmogorov-Smirnov测试。除此之外,该模型还可以通过对个人用电曲线进行卷积扩展到多个家庭。通过使用中心极限定理,可以将其分析扩展到大量家庭的一般情况。最后,与其他概率分布模型进行了简要比较,并讨论了该模型及其适用性。

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